SLAC-2017:FSM Large angular scales
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Revision as of 18:00, 28 February 2017 by Flauger (→Foregrounds, Systematics and Modeling: Large Angular Scales)
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Foregrounds, Systematics and Modeling: Large Angular Scales
Post session talks here.
- Data Challenges -- Julian Borrill File:S4 DC.pdf
- Systematics/Instrument inputs -- John Kovac
* Band selection (X=2): John/Denis, Adrian/Charlie, Jo and Reijo * idea is NOT final optimization, but only to cover representative bands to inform CDT Strawman Concept * Inclusion of systematics (X=3): [John coordinating] * idea is NOT final systematics verification, only to be representative of key challenges * "Unknown systematics residual" modeled as additive contamination, fractional level linked to N_l * Bandpass uncertainties * Pol angle uncertainty? * Noise models and bands for delensing survey (X=4) * adopt identical per-detector N_l assumptions, with higher ell_knee? Beamsize? * at some point, do we use real (S3) noise maps as basis of scaling?
CDT Instrument systematics have the following leads and groups: overall coordination: John K Beams --- Bill, Steve, Mike, John K Calibration --- polarization angles, Brian intercalibration between different angular scales, John C and Tom temporal aspects Ed Modulator systematics --- Adrian, Brian Time response --- Ed
- Analysis -- Raphael Flauger
- Longer term goal: Turn science requirements into measurement requirements with the help of data challenges - Currently a number of groups have volunteered to participate in the data challenge - David Alonson - Colin Bischoff, Victor Buza, Justin Wilmert - Hans Kristian Eriksen, Unni Fuskeland, Ingunn Wehus - Josquin Errard - Raphael Flauger - Dongwan Han, Neelima Sehgal
- Shorter term goal: Validate Fisher forecasts with DC1.0 simulations - Some first (and preliminary) results for DC1.0 from - Colin Bischoff, Victor Buza, Justin Wilmert - Josquin Errard - Raphael Flauger - DC1.0 analyses should be completed and refined, performance of different algorithms should be compared, etc.
- What should be provided for the next data challenges? - Currently the same set of simulations are used to calibrate estimators, noise bias, covariance matrix, etc. and for analyses. Should we move to one (larger and potentially less complex) set of simulations for noise bias, covariance matrix, and another (smaller) set to test algorithms, study biases, etc.?
- Wrap-Up/Discussion -- Lloyd Knox
Notes from session
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Action items/Next steps
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